Senior Backend Software Engineer, Python / Big Data / AI Code Tools

• Design and implement complex requirements for large-scale software frameworks.
• Develop and maintain libraries, frameworks, and services for big data processing.
• Build and improve components used for data pipelines on the Edison big data platform.
• Create AI code tools, agents, skills, plugins, and policies.
• Work on data lake access, data movement, GDPR compliance, retention, cleanup, metadata, and data lineage capabilities.
• Give input on framework design and architecture.
• Help resolve cross-team functional and technical dependencies.
• Maintain and support existing data engineering products.
• Contribute to the creation and onboarding of new products.
• Collaborate with other Edison teams to align solutions with the wider platform.
• Communicate with both technical and non-technical stakeholders.
• Create and execute test cases.
• Conduct self-code reviews and peer code reviews.
• Resolve incidents and defects and track them to closure.
• Execute technical integration testing with interfacing applications.

Must Have

• 5 to 7 years of software engineering experience.
• Strong Python programming experience.
• Strong understanding of programming design patterns and best practices.
• Experience in backend software development.
• Strong technical analysis and technical design skills.
• Experience with AWS cloud environments.
• Experience with AWS CI/CD tooling.
• Knowledge of AI code tools such as Claude Code or GitHub Copilot.
• Experience with CI/CD tools such as Jenkins, Bitbucket, GitHub, or Concourse.
• Good debugging and problem-solving skills.
• Ability to deliver high-quality software and releases.
• Ability to balance tactical delivery with strategic platform vision.
• Strong collaboration and cross-team communication skills.
• Ownership mindset and decision-making ability.
• Mentoring capability.
• Strong English communication.

Preferred Experience

• Experience with big data platforms.
• Experience with data engineering frameworks and reusable platform components.
• Experience with Spark, Pandas, or Polars.
• Experience with Airflow scheduling.
• Experience with data lake platforms.
• Experience with metadata, data lineage, data retention, and data cleanup capabilities.
• Experience with GDPR-related data processing requirements.
• Experience building frameworks used by data engineers or data scientists.
• Experience supporting AI workloads on cloud platforms.
• Experience working in Agile product or platform teams.